Orofacial clefts, particularly cleft lip with or without cleft palate (CL/P), are a major public health problem, affecting one in every 500-1000 births worldwide. There has been substantial recent progress by our group and others in identifying genetic loci for CL/P, confirming the suspected complexity in the genetic etiology of CL/P. As the genetic factors contributing to CL/P emerge, it is essential to identify the phenotypic characteristics attributable to each gene in order to translate the emerging research results into clinical practice. On the phenotypic side, there is emerging evidence consistent with the hypothesis that CL/P is not the sole proximate phenotype coded by the etiologic genes. There is evidence that developmental asymmetry effects may contribute to the etiology of CL/P, and that there may be unrecognized sub-clinical phenotypes in apparently unaffected relatives of individuals with clefts. The primary goal of this study is to identify the phenotypes that are segregating at a genetic level in cleft families, thereby extending the clinical phenotypie speetrum of CL/P and identifying apparently unaffected individuals who are likely to be carrying cleft genes (e.g. individuals with sub-clinical phenotypic expression). Upon meeting this goal, recurrence risk calculation and genetic counseling for this common birth defect will be vastly improved. Therefore, the specific aims of this project are to: (1) Ascertain extended multiplex families through CL/P probands served by the Pittsburgh, St. Louis and WVU cleft palate centers, as well as matched controls; (2) Obtain phenotypic measurements (including 3D craniofacial measures, orbicularis otis muscle anatomy, velopharyngeal competence, handedness, dermatoglyphics) for each multiplex family member and control; (3) Investigate combinations of phenotypes as well as the individual phenotypes; perform case-control and unaffected relative-control comparisons to identify CL/P related phenotypes, (4) Genotype all the multiplex family members and controls for a minimum of 12 candidate genes (high priority genes include IRF6, MSX1, TGFA, TGFB3, SATB2, PTCH); (5) Apply appropriate statistical genetic analysis methods to correlate phenotypes and genotype; (6) Develop a data-sharing plan to disseminate this rich data resource.